scholarly journals A Comparison of Weekly Monitoring Methods of the Palmer Drought Index

2007 ◽  
Vol 20 (24) ◽  
pp. 6033-6044 ◽  
Author(s):  
Jinyoung Rhee ◽  
Gregory J. Carbone
Keyword(s):  
South Carolina ◽  
Drought Index ◽  
Severity Index ◽  
Drought Severity ◽  
Climatic Data ◽  
Monitoring Methods ◽  
The South ◽  
Index Method ◽  
Monitoring Method ◽  
Climate Division

Abstract A method for weekly monitoring of the Palmer Drought Index (PDI) by using four parallel month-long calculation chains in rotation (“ROLLING” method) was tested for the Kansas Northwest Climate Division and the South Carolina Southern Climate Division and compared to two other methods, a modified version of the Climate Prediction Center’s weekly Palmer Drought Index monitoring method with a modified set of coefficients (“WEEKLY” method) and the National Climatic Data Center’s (NCDC’s) projected monthly Palmer Drought Index method using long-term historical daily normal temperature and precipitation (“NORMALS” method). The results for the Kansas Northwest Climate Division and the South Carolina Southern Climate Division generally agreed. The weekly method produced drought severity values that differ most from standard monthly PDI values despite using a modified set of coefficients. The method recently adopted by NCDC successfully estimated Palmer Modified Drought Index (PMDI) values late in the month, but often presented a misleading trend early in the month. The method used in this paper produced PMDI and Z Index values that approximate those found using the standard monthly PMDI code. It also preserves approximately the same length of memory found in that code, provides a tool for progressive drought monitoring allowing users to assess current drought conditions, produces a weekly historical archive of the Palmer Drought Severity Index (PDSI) and Palmer Hydrological Drought Index (PHDI), and enables users to identify the onset of drought early and more clearly.

scholarly journals Dynamical delimitation of the Central American Dry Corridor (CADC) using drought indices and aridity values

2019 ◽  
Vol 43 (5) ◽  
pp. 627-642 ◽  
Author(s):  
Luis Eduardo Quesada-Hernández ◽  
Oscar David Calvo-Solano ◽  
Hugo G Hidalgo ◽  
Paula M Pérez-Briceño ◽  
Eric J Alfaro
Keyword(s):  
Drought Index ◽  
Pacific Coast ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Rainfall Anomaly ◽  
Central American ◽  
Drought Indices ◽  
Drought Severity ◽  
Southern Mexico

The Central American Dry Corridor (CADC) is a sub-region in the isthmus that is relatively drier than the rest of the territory. Traditional delineations of the CADC’s boundaries start at the Pacific coast of southern Mexico, stretching south through Central America’s Pacific coast down to northwestern Costa Rica (Guanacaste province). Using drought indices (Standardized Precipitation Index, Modified Rainfall Anomaly Index, Palmer Drought Severity Index, Palmer Hydrological Drought Index, Palmer Drought Z-Index and the Reconnaissance Drought Index) along with a definition of aridity as the ratio of potential evapotranspiration (representing demand of water from the atmosphere) over precipitation (representing the supply of water), we proposed a CADC delineation that changes for normal, dry and wet years. The identification of areas that change their classification during extremely dry conditions is important because these areas may indicate the location of future expansion of aridity associated with climate change. In the same way, the delineation of the CADC during wet extremes allows the identification of locations that remain part of the CADC even during the wettest years and that may require special attention from the authorities.

scholarly journals A New Global 0.5° Gridded Dataset (1901–2006) of a Multiscalar Drought Index: Comparison with Current Drought Index Datasets Based on the Palmer Drought Severity Index

2010 ◽  
Vol 11 (4) ◽  
pp. 1033-1043 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
S. Beguería ◽  
J. I. López-Moreno ◽  
M. Angulo ◽  
A. El Kenawy
Keyword(s):  
Spatial Resolution ◽  
Drought Index ◽  
Palmer Drought Severity Index ◽  
National Research Council ◽  
Severity Index ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Drought Severity ◽  
Spatial And Temporal Variability ◽  
Drought Severity Index

Abstract A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI). The presented dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained using the Climatic Research Unit (CRU) TS3.0 dataset at a spatial resolution of 0.5°. The advantages of the new dataset are that (i) it improves the spatial resolution of the unique global drought dataset at a global scale; (ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI; and, in particular, (iii) it enables the identification of various drought types, given the multiscalar character of the SPEI. The dataset is freely available on the Web page of the Spanish National Research Council (CSIC) in three different formats [network Common Data Form (netCDF), binary raster, and plain text].

scholarly journals ANALISIS KEKERINGAN DI KABUPATEN SRAGEN DENGAN METODE PALMER, THORNTHWAITE, DAN STANDARDIZED PRECIPITATION INDEX

2021 ◽  
Vol 17 (2) ◽  
pp. 111-124
Author(s):  
Safrudin Nor Aripbilah ◽  
Heri Suprapto
Keyword(s):  
Drought Index ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Severity Index ◽  
Precipitation Index ◽  
Suitable Method ◽  
Drought Severity ◽  
Severe Drought ◽  
Drought Hazard ◽  
Dry Conditions

El Nino and La Nina in Indonesia are one of the reasons that caused climate changes, which has possibility of drought and flood disasters. Sragen Regency wherethe dry season occurs, drought happened meanwhile other areas experience floods and landslides. A study on drought needs to be carried out so as to reduce the risk of losses due to the drought hazard. This study is to determine the drought index in Sragen Regency based on several methods and the correlation of each methods and its suitability to the Southern Oscillation Index (SOI) and rainfall. Drought was analyzed using several methods such as Palmer Drought Severity Index (PDSI), Thornthwaite-Matter, and Standardized Precipitation Index (SPI) then correlated with SOI to determine the most suitable method for SOI. The variables are applied in this method are rainfall, temperature, and evapotranspiration. The results showed that the drought potential of the Palmer method is only in Near Normal conditions, which is 1%, Severe drought conditions are 29% for the Thornthwaite-Matter method, and Extreme Dry conditions only reach 1,11% for the SPI method. The PDSI and SPI methods are inversely proportional to the Thornthwaite-Matter method and the most suitable method for SOI values or rainfall is the SPI method. These three methods can be identified the potential for drought with only a few variables so that they could be applied if they only have those data.Keywords: Drought, PDSI, Thornthwaite-Matter, SPI, SOI

scholarly journals Selection Drought Index Calculation Methods Using Electre, Topsis, and Analytic Hierarchy Process

2018 ◽  
Vol 7 (4.44) ◽  
pp. 188
Author(s):  
Hadisuwito A.S ◽  
Hassan F.H
Keyword(s):  
Analytic Hierarchy Process ◽  
Forest Fires ◽  
Drought Index ◽  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Drought Severity ◽  
Analytic Hierarchy ◽  
Forest Fire Danger ◽  
The Right ◽  
Hierarchy Process

The drought index is an essential indicator for calculating forest fires’ potential. Many methods are developed to maintain the drought index. However, they provide less suitable at many places. Every area has their own character, and each of methods has their own specification. The spot problem is how to find the right method for those places. The forest of Bukit Suharto, has particular character as one of the rain tropical forests, and it needs suitable method. Furthermore, this study is conducted to examine the right methods that compatible for the forest. They are: Palmer Drought Severity Index (PDSI), Keetch Byram Drought Index (KBDI), Reconnaissance Drought Index (RDI), Standard Precipitation Index (SPI), Effective Drought Index (EDI), McArthur Forest Fire Danger Index (MFFDI), and Standard Precipitation Evapotranspiration Index (SPEI). Every method has specific variables for the calculation, namely, the period, the data’s type, the formula’s complexity, the usability, and scale results’ type. On processing the seven methods, the researcher uses other techniques to asses them, namely, ELECTRE, TOPSIS, and Analytic Hierarchy Process. In final process, the conclusion is compared through the result. In summary, the results show that KBDI’s method is the most recommended, and TOPSIS is the best technique for recommendations. 

Drought monitoring incorporating precipitation and climate variables and its application for future drought projection

2020 ◽  
Author(s):  
Jeongeun Won ◽  
Sangdan Kim
Keyword(s):  
Drought Index ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Management Program ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Drought Severity ◽  
Climate Variables ◽  
Evaporative Demand ◽  
Monitoring Method

<p>In drought monitoring, it is very important to select climate variables to interpret drought. Most drought monitoring interprets drought as deficit in precipitation, so drought indices focused on the moisture supply side of the atmosphere have been mainly used. However, droughts can be caused not only by lack of rainfall, but also by various climate variables such as increase in temperature. In this regard, interest in potential evapotranspiration(PET), which is an moisture demand side of the atmosphere, is increasing and a PET-based drought index has been developed. However, complex droughts caused by various climate variables cannot be interpreted as a drought index that only considers precipitation or PET. In this study, we suggest a drought monitoring method that can reflect various future climate variables, including precipitation. In other words, copula-based joint drought index(CJDI), which incorporate standardized precipitation index(SPI) based on precipitation and evaporative demand drought index(EDDI) based on PET, is developed. CJDI, which considers both precipitation and PET, which are key variables related to drought, is able to properly monitor the drought events in Korea. In addition, future Drought severity – duration - frequency curves are derived to project future droughts compared to various drought indices. It is shown that CJDI can be used as a more reasonable drought index to establish the adaptation policy for future droughts by presenting the pattern of future droughts more realistically.</p><p><strong>Acknowledgment: </strong>This study was funded by the Korea Ministry of Environment (MOE) as Smart Urban Water Resources Management Program. (2019002950004)</p><p><strong>Keywords</strong>: Climate change; Copula; Drought; CJDI; Drought severity-duration-frequency curve</p>

Revisiting drought trend over China during 1948-2016: a multivariate perspective

2020 ◽  
Author(s):  
Liliang Ren
Keyword(s):  
Drought Index ◽  
Potential Evapotranspiration ◽  
Severity Index ◽  
Northeastern China ◽  
Trend Detection ◽  
Drought Indices ◽  
Drought Severity ◽  
Main Driver ◽  
Land Data Assimilation System ◽  
The Individual

<p><span><span lang="EN-US">How drought changes in the context of global warming </span><span lang="EN-US">is a concerning issue that influences the strategies of drought mitigation and drought management.</span><span lang="EN-US"> Based on the simulations of the </span><span lang="EN-US">version 2 of Global Land Data Assimilation System (GLDAS-2.0) during 1948-2016</span><span lang="EN-US">, we revisited the drought trend over China and analyzed the individual contributions of precipitation and potential evapotranspiration (PET) on varied drought patterns. Four composite drought indices including the </span><span lang="EN-US">Aggregate Drought Index (ADI)</span><span lang="EN-US">, </span><span lang="EN-US">Joint Drought Deficit Index (JDI), self-calibrating Palmer Drought Severity Index (scPDSI) and Standardized Palmer Drought Index (SPDI) were employed for trend detection. Results showed that all four composite drought indices suggested a significant drying belt spreads from northeastern China to southwestern China, and a significant wetting trend in the “Three river sources” areas. Controversial patterns were mainly located in the northwestern China, Xinjiang districts, and the middle and lower reaches of the Yangtze River, where the SPDI and JDI respectively, overestimated and underestimated the moisture conditions at varying degrees. According to the change point tests, it is found that the drying pattern in the northeastern China occurred since 1970s, where precipitation deficits and expanded PET jointly aggravated the drying process, while for the “Three river sources” areas, the increased precipitation since 2000s is the main driver for the wetting pattern.</span></span></p>

scholarly journals A Global Gridded Dataset of GRACE Drought Severity Index for 2002–14: Comparison with PDSI and SPEI and a Case Study of the Australia Millennium Drought

2017 ◽  
Vol 18 (8) ◽  
pp. 2117-2129 ◽  
Author(s):  
Meng Zhao ◽  
Geruo A ◽  
Isabella Velicogna ◽  
John S. Kimball
Keyword(s):  
Water Storage ◽  
Severity Index ◽  
Drought Monitoring ◽  
Drought Severity ◽  
Terrestrial Water Storage ◽  
Monitoring Methods ◽  
Millennium Drought ◽  
Eastern Australia ◽  
Terrestrial Water ◽  
Drought Severity Index

Abstract A new monthly global drought severity index (DSI) dataset developed from satellite-observed time-variable terrestrial water storage changes from the Gravity Recovery and Climate Experiment (GRACE) is presented. The GRACE-DSI record spans from 2002 to 2014 and will be extended with the ongoing GRACE and scheduled GRACE Follow-On missions. The GRACE-DSI captures major global drought events during the past decade and shows overall favorable spatiotemporal agreement with other commonly used drought metrics, including the Palmer drought severity index (PDSI) and the standardized precipitation evapotranspiration index (SPEI). The assets of the GRACE-DSI are 1) that it is based solely on satellite gravimetric observations and thus provides globally consistent drought monitoring, particularly where sparse ground observations (especially precipitation) constrain the use of traditional model-based monitoring methods; 2) that it has a large footprint (~350 km), so it is suitable for assessing regional- and global-scale drought; and 3) that it is sensitive to the overall terrestrial water storage component of the hydrologic cycle and therefore complements existing drought monitoring datasets by providing information about groundwater storage changes, which affect soil moisture recharge and drought recovery. In Australia, it is demonstrated that combining GRACE-DSI with other satellite environmental datasets improves the characterization of the 2000s “Millennium Drought” at shallow surface and subsurface soil layers. Contrasting vegetation greenness response to surface and underground water supply changes between western and eastern Australia is found, which might indicate that these regions have different relative plant rooting depths.

scholarly journals The Novel Microwave Temperature Vegetation Drought Index (MTVDI) Captures Canopy Seasonality across Amazonian Tropical Evergreen Forests

2021 ◽  
Vol 13 (3) ◽  
pp. 339
Author(s):  
Liyang Liu ◽  
Xueqin Yang ◽  
Fanxi Gong ◽  
Yongxian Su ◽  
Guangqing Huang ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Drought Index ◽  
Vegetation Index ◽  
Severity Index ◽  
Evergreen Forest ◽  
Mean Annual Precipitation ◽  
Drought Severity ◽  
Earth Observing System ◽  
Tropical Evergreen Forest ◽  
Terrestrial Water

Despite its perennial canopy, the Amazonian tropical evergreen forest shows significant canopy growth seasonality, which has been represented by optical satellite-based observations. In this paper, a new Microwave Temperature–Vegetation Drought Index (MTVDI) based on Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) sensors was used to capture the canopy seasonality from 2003 to 2010 in comparison with four climatic dryness indicators (Palmer Drought Severity Index (PDSI), Climatological Water Deficit (CWD), Terrestrial Water Storage (TWS), Vapor Pressure Deficit (VPD)) and two photosynthesis proxies (Enhanced Vegetation Index (EVI) and Solar-Induced chlorophyll Fluorescence (SIF)), respectively. Our results suggest that the MTVDI shows opposite seasonal variability with two photosynthesis proxies and performs better than the four climatic dryness indicators in reflecting the canopy photosynthesis seasonality of tropical forests in the Amazon. Besides, the MTVDI captures wet regions that show green-up during the dry season with mean annual precipitation higher than 2000 mm per year. The MTVDI provides a new way for monitoring the canopy seasonality of tropical forests from microwave signals.

scholarly journals Effects of Climatic and Soil Data on Soil Drought Monitoring Based on Different Modelling Schemes

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 913
Author(s):  
Jan Řehoř ◽  
Rudolf Brázdil ◽  
Miroslav Trnka ◽  
Milan Fischer ◽  
Jan Balek ◽  
...  
Keyword(s):  
Soil Property ◽  
Palmer Drought Severity Index ◽  
Severity Index ◽  
Drought Monitoring ◽  
Balance Model ◽  
Drought Severity ◽  
Soil Drought ◽  
Climatic Data ◽  
The Czech Republic ◽  
Drought Occurrence

Satisfactory requirements for the spatial resolution of climate and the influences of soil data in defining the starting points, endings, and the intensities of droughts have become matters of discussion in recent years. The overall inclusiveness of the modelling tools applied is also frequently discussed. In this light, five model setups (MSs) of the daily SoilClim water balance model were developed and tested for the Czech Republic (CR) in the 1961–2020 period. These included two versions of the SoilClim model, two sets of soil data, and two sets of climatic data at different spatial resolutions. MS1–MS4 were based on local, spatially-interpolated data from meteorological stations (500 × 500 m resolution), while MS5 was developed for global drought monitoring, based on the coarser ERA5-Land reanalysis (0.1° × 0.1°). During the 1961–2020 period, all the MSs indicated strong, statistically significant increases in the occurrence of 10th-percentile soil drought in the April–June season; however, trends remained largely non-significant for the remainder of the year. Variations among MS1–MS4 demonstrate that the range of soil property input data affects results to a lesser extent than different modelling schemes. The major simplification of the model grid in MS5 still led to an acceptable conformity of results, while the non-conformities disclosed may be explained by differences between meteorological inputs. Comparison with the Palmer Drought Severity Index (PDSI) confirmed that the SoilClim model depicts the variability of soil drought occurrence in greater detail, while PDSI tends to highlight the most severe events. The discussion arising out of the study centers around model uncertainties and the expression of soil drought episodes in different MSs.

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